TL;DR – We’re excited to introduce voyage-context-3, a contextualized chunk embedding model that produces vectors for chunks that capture the full document context without any manual metadata and context augmentation, leading to higher retrieval accuracies than with or without augmentation. It’s also simpler, faster and cheaper, and is a drop-in replacement for standard embeddings without downstream workflow changes, also reducing chunking strategy sensitivity. On chunk-level and document-level ...